Al Sahel vs Kazma: result 1-2 and analysis
Premier LeagueRegular Season - 5Kick-off on October 4, 2013 at 02:50 PM (UTC)Al Sahel Stadium, Abu Halifa
Full time
What was the result of Al Sahel vs Kazma?
Kazma won 1-2 on October 4, 2013.
Goalscorers
- 29′Saeed Mohammad Saeed Hasan Al MurjanKazma
- 42′Nasser Al HajriAl Sahel
- 86′Saeed Mohammad Saeed Hasan Al MurjanKazma
What is the recent form of both teams?
Over their last 4 matches in all competitions, Al Sahel have 1 win, 0 draws and 3 defeats; Kazma have 2, 4 and 9.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 27, 2013 | Al Fahaheel(away) | 1-0 | Premier League |
| Sep 21, 2013 | Al Nasar(away) | 3-4 | Premier League |
| Sep 13, 2013 | Al Qadsia(home) | 0-1 | Premier League |
| Aug 30, 2013 | Khaitan(home) | 0-1 | Premier League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 27, 2013 | Al Nasar(home) | 0-0 | Premier League |
| Sep 20, 2013 | Al Salmiyah(away) | 1-3 | Premier League |
| Sep 13, 2013 | Al Kuwait(away) | 0-1 | Premier League |
| Aug 30, 2013 | Al Arabi(home) | 1-1 | Premier League |
| Apr 19, 2013 | Al Arabi(away) | 0-3 | Premier League |
How many goals should we expect?
Al Sahel score 1.0 and concede 1.5 goals per match over their last 4; Kazma score 0.5 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Al Sahel | 1.0 | 1.5 | 1 | 1/4 | 1/4 |
| Kazma | 0.5 | 1.3 | 5 | 4/15 | 4/15 |
Over the last 4 matches in all competitions.
Where do both teams sit in the table?
Al Sahel sit 9th in Premier League (4 points from 4 matches) and Kazma sit 5th (8 points from 4 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 5 | Kazma | 4 | 2 | 2 | 0 | 7 | 4 | 8 |
| 9 | Al Sahel | 4 | 1 | 1 | 2 | 1 | 5 | 4 |
A question about Al Sahel vs Kazma?
Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.
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How does Footlab AI compute this prediction?
The model combines both teams' Elo ratings (anchored by competition pool), their recent form weighted by opponent strength, home advantage and a Poisson matrix for scorelines. When bookmakers publish odds for the match, their consensus is built into the calculation: that is what proved most accurate on past matches. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy